Armed with new data showing black applicants suffer a 35% lower chance of having a grant proposal funded than their white counterparts, NIH officials are gearing up to test whether reviewers in its study sections give lower scores to proposals from African-American applicants. They say it’s one of several possible explanations for a disparity in success rates first documented in a 2011 report by a team led by economist Donna Ginther of the University of Kansas, Lawrence.

Huh. 35%? I thought Ginther estimated more like a 13% difference? Oh wait. That's the award probability difference. About 16% versus 29% for white applicants which would be about a 45% lower chance. And this shows "78-90% the rate of white...applicants". And there was Nakamura quoted in another piece in Science:

At NIH, African-American researchers “receive awards at “55% to 60% the rate of white applicants,” Nakamura said. “That's a huge disparity that we have not yet been able to seriously budge,” despite special mentoring and networking programs, as well as an effort to boost the number of scientists from underrepresented minorities who evaluate proposals.

Ginther..noted...black researchers are more likely to have their applications for an R01 grant—the bread-and-butter NIH award that sustains academic labs—thrown out without any discussion...black scientists are less likely to resubmit a revised proposal ...whites submit at a higher rate than blacks...

So, what is CSR doing about it now? OK HOLD UP. LET ME REMIND YOU IT IS FIVE YEARS LATER. FIFTEEN FUNDING ROUNDS POST-GINTHER. Ahem.

The bias study would draw from a pool of recently rejected grant applications that have been anonymized to remove any hint of the applicant’s race, home institution, and training. Reviewers would be asked to score them on a one-to-nine scale using NIH’s normal rating system.

It's a start. Of course, this is unlikely to find anything. Why? Because the bias at grant review is a bias of identity. It isn't that reviewers are biased against black applicants, necessarily. It is that they are biased for white applicants. Or at the very least they are biased in favor of a category of PI ("established, very important") that just so happens to be disproportionately white. Also, there was this interesting simulation by Eugene Day that showed a bias that is smaller than the non-biased variability in a measurement can have large effects on something like a grant funding system [JournalLink].

Ok, so what else are they doing?

NIH continues to wrestle with the implications of the Ginther report. In 2014, in the first round of what NIH Director Francis Collins touted as a 10-year, $500 million initiative to increase the diversity of the scientific workforce, NIH gave out 5-year, $25 million awards to 10 institutions that enroll large numbers of minority students and created a national research mentoring network.

As you know, I am not a fan of these pipeline-enhancing responses. They say, in essence, that the current population of black applicant PIs is the problem. That they are inferior and deserve to get worse scores at peer review. Because what else does it mean to say the big money response of the NIH is to drum up more black PIs in the future by loading up the trainee cannon now?

This is Exhibit A of the case that the NIH officialdom simply cannot admit that there might be unfair biases at play that caused the disparity identified in Ginther and reinforced by the other mentioned analyses. The are bound and determined to prove that their system is working fine, nothing to see here.

So....what else ?

A second intervention starting later this year will tap that fledgling mentoring network to tutor two dozen minority scientists whose R01 applications were recently rejected. The goal of the intervention, which will last several months, is to prepare the scientists to have greater success on their next application. A third intervention will educate minority scientists on the importance of resubmitting a rejected proposal, because resubmitted proposals are three times more likely to be funded than a de novo application from a researcher who has never been funded by NIH.

Oh ff..... More of the same. Fix the victims.

Ah, here we go. Mervis finally gets around to explaining that 35% number

NIH officials recently updated the Ginther study, which examined a 2000–2006 cohort of applicants, and found that the racial disparity persists. The 35% lower chance of being funded comes from tracking the success rates of 1054 matched pairs of white and black applicants from 2008 to 2014. Black applicants continue to do less well at each stage of the process.

I wonder if they will be publishing that anywhere we can see it?

But here's the kicker. Even faced with the clear evidence from their own studies, the highest honchos still can't see it.

One issue that hung in the air was whether any of the disparity was self-inflicted. Specifically, council members and NIH officials pondered the tendency of African-American researchers to favor certain research areas, such as health disparities, women’s health, or hypertension and diabetes among minority populations, and wondered whether study sections might view the research questions in those areas as less compelling. Valantine called it a propensity “to work on issues that resonate with their core values.” At the same time, she said the data show minorities also do less well in competition with their white peers in those fields.

Collins offered another possibility. “I’ve heard stories that they might have been mentored to go into those areas as a better way to win funding,” he said. “The question is, to what extent is it their intrinsic interest in a topic, and to what extent have they been encouraged to go in that direction?”

Look, Ginther included a huge host of covariate analyses that they conducted to try to make the disparity go away. Now they've done a study with matched pairs of investigators. Valantine's quote may refer to this or to some other analysis I don't know but obviously the data are there. And Collins is STILL throwing up blame-the-victim chaff.

Dude, I have to say, this kind of denialist / crank behavior has a certain stench to it. The data are very clear and very consistent. There is a funding disparity.

This is a great time to remind everyone that the last time a major funding disparity came to the attention of the NIH it was the fate of the early career investigators. The NIH invented up the ESI designation, to distinguish it from the well established New Investigator population, and immediately started picking up grants out of the order of review. Establishing special quotas and paylines to redress the disparity. There was no talk of "real causes". There was not talk of strengthening the pipeline with better trainees so that one day, far off, they magically could better compete with the established. Oh no. They just picked up grants. And a LOT of them.

I wonder what it would take to fix the African-American PI disparity...

Ironically, because the pool of black applicants is so small, it wouldn’t take much to eliminate the disparity: Only 23 more R01 applications from black researchers would need to be funded each year to bring them to parity.

In that 175 bin we'd need 3 more African-American PI apps funded to get to 100%. In the next higher (worse) scoring bin (200 score), about 56% of White PI apps were funded. Taking three from this bin and awarding three more AA PI awards in the next better scoring bin would plunge the White PI award probability from 56% to 55.7%. Whoa, belt up cowboy.

Moving down the curve with the same logic, we find in the 200 score bin that there are about 9 AA PI applications needed to put the 200 score bin to 100%. Looking down to the next worse scoring bin (225) and pulling these 9 apps from white PIs we end up changing the award probability for these apps from 22% to ..wait for it..... 20.8%.

Mere handfuls. I had probably overestimated how many black PIs were seeking funding. If this Mervis piece is to be trusted and it would only take 23 pickups across the entire NIH to fix the problem....

I DON'T UNDERSTAND WHAT FRANCIS COLLINS' PROBLEM IS.

Twenty three grants is practically rounding error. This is going to shake out to one or maybe three grants per year for the ICs, depending on size and what not.

Heck, I bet they fund this many grants every year by mistake. It's a big system. You think they don't have a few whoopsies sneak by every now and again? Of course they do.

But god forbid they should pick up 23 measly R01s to fix the funding disparity.

The NIH director and the heads of ICs are in thrall to the BSDs that want everybody to believe that they won the meritocracy game fair and square, denying their enormous privilege to date. This circling of the wagons around the illusion of merit is the biggest obstacle facing any effort for greater inclusion and diversity in science. The Republican Congress is just a boogeyman.

@Dusanbe, they may well be using merit to make their decisions. It is just that their criteria for meritorious applicants is probably based on benchmarks that are historically easier for rich, white people to achieve.

the proclaimed IQ scale in descending order is: Chinese, white, hispanics, blacks. So that policies would tend to weight pro and against that, depending on the society view of the time. (the small bias?)

But I think science programs also reflect the needs of the time so that the qualifier of race competes with the misnomer of 'minority' because of the part of money contributed by people in need of the applied research findings.

Real peace and abundant work that is rewarded according to effort and tangible contributions sounds like the needed fertilizer for a science program to fluourish and yield the best products and seeds. That should be the task, but it just doesn't happen easily, wonder why?.

I usually lurk on this blog, but I can't resist commenting on these NIH efforts:

1) Interesting initiative to review "blinded" grant applications but I think it would be difficult in practice to blind reviewers to the applicants.
2) Couldn't NIH use internal data to conduct a decomposition analysis of the observed racial disparities in scoring? It seems like an appropriate application of the method to determine the extent to which observed characteristics of investigators (e.g., institution, training, productivity) explain disparities and how much unexplained variation is to to unobserved factors (i.e., racism). Such results would provide empirical evidence to support interventions.
3) Could NIH conduct a study in which a random sample of study section members take an implicit bias test?

With the NIH push to improve rigor and ensure appropriate blinding in experiments, I really wish the organization would follow its own dictate and blind all research applications as well. Reviewers should be blinded to both the applicant PI(s) as well as institution(s) and collaborator(s) and review just the proposed science. As an NIH PO, I'm sick and tired of reviewers automatically giving good impact scores just based on the reputation of the applicant PI. Some of the PIs' reputation was built on achievements from decades ago, but may have "slipped" in recent years but that decline is almost universally ignored.

The problem is that it can't be done MBster. Unless we have a radical upheaval of how grants are written and reviewed.

Beyond tactical and practical concerns, I have a question. Why are Investigator and Environment two of the major review categories? I honestly don't know why, how or when NIH review decided that these are, formally speaking, co-equal with Approach or Significance.

DM - Investigator and environment are co-equal factors (although they are not really, since environment at least has very little correlation to impact score) because these are grants not contracts - so part of the question is whether the money will be well-spent even if the "project takes a hard turn". Also, we need to know that the investigator can do the project, particularly the open-endedness that is science.

I like to think of this as "people doing projects".

Personally, I'd like to see more people not projects, because it would bring us back to entry and renewal rather than trying to pick the best "project" that isn't really going to be done that way anyway.

Of course, that suggests NIH program should be using additional criteria to pick up projects on the margins, which they do anyway. So, I agree with your original point that they should just acknowledge and solve Ginther by picking up extra grants at the margins.

Don't forget, part of the reason funded (HHMI) people are successful is because they got funded!

I can't see blinding applications working at all. In the last year I reviewed two manuscripts that were blinded with regard to the author and institution. However, I knew exactly who had written the articles. The whole thing was silly.

Why even have individual criterion scoring at all? They don't figure into the preliminary priority impact score that determines whether the app will be discussed at the meeting and are not adjusted post-discussion either.

Anyway, this is an interesting pub that just came out that may be of interest - "How Criterion Scores Predict the Overall Impact Score and Funding Outcomes for National Institutes of Health Peer-Reviewed Applications" - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4889138/

Poor Francis Collins.
He no longer has anything to offer in Science so he spends
his time spewing out misleading Demographic information
in order to prove he's politically correct. Truth is the whole Science funding
and Science career pipeline is a Big Stinking Mess and needs to be revamped.
Why isn't he talking about that?

From yesterday's issue of Science, about the NIH Early Career Review (ECR) program...

"But Nakamura worries that asking minority scientists to play a bigger role in NIH’s grantsmaking process could distract them from building up their lab, finding stable funding, and earning tenure. Serving on a study section, he says, means that “those individuals will have less time to write applications. So we need to strike the right balance.”

Not that I ever had a lot of it, but my respect for biological scientists takes another knock after reading this post.

As you say, 23 applications is a rounding error. So, funding 23 extra applications doesn't fix any problem, because there is no problem to begin with! You said it yourself, its a rounding error...meaning that it is not statistically significant.

It is pathetic that tenured professors in biology do not even have the mathematical reasoning skills of an undergraduate math major finishing the first semester of college. People, if your work requires math/stat, please learn this stuff before you go around using it like a drunk uses a lamp post. I shudder to think that people of your caliber are working on fields that have direct impact on medicine.